import pandas as pd
import numpy as np
import tensorflow as tf


def create_pair_demand():
    proba = np.random.random()
    if proba < 0.8:
        pair_demand = np.random.normal(150, 20)
    else:
        pair_demand = np.random.normal(400, 20)
    return pair_demand


def create_single_DM_matrix(n):
    DM_matrix=np.zeros((1,n*n))
    for i in range(0,n*n):
        DM_matrix[:i]=create_pair_demand()
    datas=sparse_DM_matrix(1, DM_matrix)
    df = pd.DataFrame(datas)
    print(df)
    return df


def sparse_DM_matrix(p,dm_matrix):
    return  dm_matrix


_df=create_single_DM_matrix(3)
_df.to_csv('input_data.csv')


